The sustainable development of an organisation requires a holistic approach to the evaluation of an enterprise’s goals and activities. The essential means enabling an organisation to achieve goals are business processes. Properly managed, business processes are a source of revenue and become an implementation of business strategy. The critical elements in process management in an enterprise are process monitoring and control. It is therefore essential to identify the Key Performance Indicators (KPIs) that are relevant to the analysed processes. Process monitoring can be performed at various levels of management, as well as from different perspectives: operational, financial, security, or maintenance. Some of the indicators known from other fields (such as personnel management, finance, or lean manufacturing) can be used in mining. However, the operational mining processes require a definition of specific indicators, especially in the context of increasing the productivity of mining machines and the possibility of using sensor data from machines and devices. The article presents a list of efficiency indicators adjusted to the specifics and particular needs of the mining industry resulting from the Industry 4.0 concept, as well as sustainable business performance. Using the conducted research and analysis, a list of indicators has been developed concerning person groups, which may serve as a benchmark for mining industry entities. The presented proposal is a result of work conducted in the SmartHUB project, which aims to create an Industrial Internet of Things (IIoT) platform that will support process management in the mining industry.

Review of Key Performance Indicators for Process Monitoring in the Mining Industry

The modern mining industry is full of unique solutions for the implementation of key performance indicators accounting. The task of the mining enterprise, like any business, is to make a profit. An important role in assessing the performance of a mining enterprise is played by performance indicators combined into a system called KPI. The system for setting and recording key indicators developed by specialists from the D.A. Kunaev Institute of Mining The main task of this system of indicators is to assess the effectiveness of the company, aimed at achieving the main strategic goals and objectives. Thanks to the system of setting and recording key indicators, it is possible to assess the strengths and weaknesses of the enterprise, as well as understand what factors negatively affect and inhibit the development process. The use of the system for setting and recording key performance indicators allows:  To ensure transparency and predictability of technological and organizational processes of the company due to a properly built process of digitalization of the system for setting and recording key indicators.  To assess the quality of work of each employee / project / company.  To focus the activities of all departments on priority tasks.  To form an honest and effective system of staff motivation to achieve super-results.  To increase the level of responsibility for the result of each employee involved in the project.  When dismissing or replacing specialists, to use the accumulated information to train new employees in the workplace. To implement this accounting, in the process of designing the system, universal digital technologies were integrated, which made it possible to keep records of inventories, determine the positioning of personnel, etc. It should be noted that the project for the implementation of this system in small, medium and large businesses will have its own characteristics and priorities.

/pdf/digitalization-of-technological-and-organizational-processes-3k05by4n08.pdf

Digitalization of technological and organizational processes of mining operations due to the implementation of the installation system and accounting the key indicators

Underground production scheduling with ventilation and refrigeration considerations

This work presents a model for determining the availability of continuous systems at open pits by applying fuzzy logic and fuzzy inference systems. The applied model was formed by the synthesis of independent partial indicators of availability. The model is based on an expert system for assessing the availability of continuous mining systems. The availability of the system, as a complex state parameter, is decomposed into the partial indicators, reliability, and convenience of maintenance, and the fuzzy compositions, used for integration the partial indicators, are the max–min and min–max compositions. The advantage of this model in comparison to the conventional models is that it takes into account the effect of practical indicators of availability, does not require long-term monitoring, and records necessary to determine the time picture of the system state. This model for determining the availability has a role to help responsible persons at open pits in the planning and control of exploitation, and the adoption of an appropriate maintenance strategy, all with the aim of stable production and cost reduction. The presented model can be used as a tool for the quick assessment of system availability, based on expert judgments and assessments.

/pdf/determining-the-availability-of-continuous-systems-at-open-1xw0zh39.pdf

Determining the Availability of Continuous Systems at Open Pits Applying Fuzzy Logic

A mining production system (MPS) is a result of an iterative process of design, planning, and optimization of mining input variables and decision-making variables (DMVs). The MPS exists within the mineral extraction link of the complete mining value chain. It represents the stage where mining companies have the opportunity, through production, to start generating returns on the investments undertaken. Returns on shareholders’ investments can be realized at this stage. More often than not, the actual performance of the MPS is somewhat different to that in the optimized MPS plan. This behaviour or characteristic is observed in an ensemble of output results of the key performance indicators (KPIs). These results are sometimes above target, on target, or below target due to uncertainty associated with technical and human factors, resulting in actual output being different to that planned. The first two circumstances are perhaps the most desired. However, in most cases the MPS, especially in the case of mature mines, tends to deliver below target. The variability of the KPIs of interest is influenced by internal variables or DMVs. The variable units or DMVs can be either controllable or uncontrollable. It is therefore important to understand and know to what degree the controllable variables can be controlled to achieve the desired output and to minimize the effects of the uncontrollable variables. This paper is part of an MSc research study at the University of the Witwatersrand, based on a platinum mine MPS case study where actual data was available for analysis.

/pdf/characterizing-a-mining-production-system-for-decision-4phaj5ltly.pdf

Characterizing a mining production system for decision-making purposes in a platinum mine

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Characterizing a mining production system for decision-making purposes in a platinum mine